José Celso Rocha

741 total citations
42 papers, 515 citations indexed

About

José Celso Rocha is a scholar working on Public Health, Environmental and Occupational Health, Pediatrics, Perinatology and Child Health and Reproductive Medicine. According to data from OpenAlex, José Celso Rocha has authored 42 papers receiving a total of 515 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Public Health, Environmental and Occupational Health, 7 papers in Pediatrics, Perinatology and Child Health and 5 papers in Reproductive Medicine. Recurrent topics in José Celso Rocha's work include Reproductive Biology and Fertility (15 papers), Assisted Reproductive Technology and Twin Pregnancy (7 papers) and Ovarian function and disorders (5 papers). José Celso Rocha is often cited by papers focused on Reproductive Biology and Fertility (15 papers), Assisted Reproductive Technology and Twin Pregnancy (7 papers) and Ovarian function and disorders (5 papers). José Celso Rocha collaborates with scholars based in Brazil, Spain and United Kingdom. José Celso Rocha's co-authors include Marcelo Fábio Gouveia Nogueira, Eutímio Gustavo Fernández Núñez, M Takahashi, Andréa Cristina Basso, Cristina Hickman, Aldo Tonso, Marcos Meseguer, Lorena Bori, Sérgio Catanozi and Marisa Passarelli and has published in prestigious journals such as Scientific Reports, Diabetologia and Sensors.

In The Last Decade

José Celso Rocha

40 papers receiving 500 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
José Celso Rocha Brazil 13 218 116 97 91 41 42 515
Xingting Liu China 15 65 0.3× 52 0.4× 13 0.1× 184 2.0× 62 1.5× 49 648
Anna Koziorowska Poland 12 42 0.2× 16 0.1× 12 0.1× 85 0.9× 21 0.5× 41 378
Yichen He China 13 64 0.3× 33 0.3× 41 0.4× 118 1.3× 10 0.2× 36 536
Tarun Kumar Ghosh India 10 39 0.2× 18 0.2× 20 0.2× 18 0.2× 8 0.2× 35 474
Menghui Li China 16 51 0.2× 61 0.5× 35 0.4× 74 0.8× 4 0.1× 30 575
Caihong Wu China 11 129 0.6× 108 0.9× 9 0.1× 138 1.5× 34 0.8× 25 425
Amena Khatun Bangladesh 13 94 0.4× 135 1.2× 16 0.2× 64 0.7× 39 1.0× 19 360
Mohamed Slaoui France 6 18 0.1× 17 0.1× 11 0.1× 91 1.0× 28 0.7× 11 466
R. Parameswari India 9 54 0.2× 93 0.8× 6 0.1× 29 0.3× 4 0.1× 46 262

Countries citing papers authored by José Celso Rocha

Since Specialization
Citations

This map shows the geographic impact of José Celso Rocha's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by José Celso Rocha with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites José Celso Rocha more than expected).

Fields of papers citing papers by José Celso Rocha

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by José Celso Rocha. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by José Celso Rocha. The network helps show where José Celso Rocha may publish in the future.

Co-authorship network of co-authors of José Celso Rocha

This figure shows the co-authorship network connecting the top 25 collaborators of José Celso Rocha. A scholar is included among the top collaborators of José Celso Rocha based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with José Celso Rocha. José Celso Rocha is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Lourenço, Bárbara Hatzlhoffer, et al.. (2025). MAIA platform for routine clinical testing: an artificial intelligence embryo selection tool developed to assist embryologists. Scientific Reports. 15(1). 32273–32273.
2.
3.
Nogueira, Marcelo Fábio Gouveia, José Celso Rocha, João Diego de Agostini Losano, et al.. (2023). Can in vitro embryo production be estimated from semen variables in Senepol breed by using artificial intelligence?. Frontiers in Veterinary Science. 10. 1254940–1254940. 6 indexed citations
4.
Bori, Lorena, et al.. (2022). An Image Processing Protocol to Extract Variables Predictive of Human Embryo Fitness for Assisted Reproduction. Applied Sciences. 12(7). 3531–3531. 3 indexed citations
5.
6.
Bori, Lorena, Francisco Domı́nguez, Raquel Del Gallego, et al.. (2020). An artificial intelligence model based on the proteomic profile of euploid embryos and blastocyst morphology: a preliminary study. Reproductive BioMedicine Online. 42(2). 340–350. 47 indexed citations
7.
Nogueira, Marcelo Fábio Gouveia, et al.. (2020). Artificial intelligence in the IVF laboratory: overview through the application of different types of algorithms for the classification of reproductive data. Journal of Assisted Reproduction and Genetics. 37(10). 2359–2376. 66 indexed citations
8.
Takahashi, M, et al.. (2019). Brewing process optimization by artificial neural network and evolutionary algorithm approach. Journal of Food Process Engineering. 42(5). 11 indexed citations
9.
Meseguer, Marcos, et al.. (2019). Is there any room to improve embryo selection? artificial intelligence technology applied for ive birth prediction on blastocysts. Fertility and Sterility. 112(3). e77–e77. 1 indexed citations
10.
Meseguer, Marcos, Nikica Zaninović, T. L. Wilkinson, et al.. (2018). Using artificial intelligence (AI) and time-lapse to improve human blastocyst morphology evaluation. Human Reproduction. 125–126. 2 indexed citations
11.
Rocha, José Celso, et al.. (2018). Use of ultraviolet–visible spectrophotometry associated with artificial neural networks as an alternative for determining the water quality index. Environmental Monitoring and Assessment. 190(6). 319–319. 20 indexed citations
12.
Rocha, José Celso, et al.. (2017). Rapid monitoring of beer-quality attributes based on UV-Vis spectral data. International Journal of Food Properties. 1–14. 7 indexed citations
13.
Rocha, José Celso, et al.. (2017). Using artificial intelligence to improve blastocyst morphology evaluation. Human Reproduction. 72–73. 2 indexed citations
14.
Rocha, José Celso, et al.. (2017). A Method Based on Artificial Intelligence To Fully Automatize The Evaluation of Bovine Blastocyst Images. Scientific Reports. 7(1). 7659–7659. 46 indexed citations
15.
Rocha, José Celso, et al.. (2017). Automatized image processing of bovine blastocysts produced in vitro for quantitative variable determination. Scientific Data. 4(1). 170192–170192. 19 indexed citations
16.
Neto, Pedro de Oliva, et al.. (2016). Artificial intelligence approach based on near-infrared spectral data for monitoring of solid-state fermentation. Process Biochemistry. 51(10). 1338–1347. 24 indexed citations
17.
Nogueira, Marcelo Fábio Gouveia, et al.. (2014). Artificial intelligence meets the same challenges as humans in morphological classification of bovine blastocysts. Animal Reproduction. 11(3). 489–489. 1 indexed citations
18.
Takahashi, M, et al.. (2014). Artificial neural network associated to UV/Vis spectroscopy for monitoring bioreactions in biopharmaceutical processes. Bioprocess and Biosystems Engineering. 38(6). 1045–1054. 45 indexed citations
19.
Zulantay, Inés, Werner Apt, José Celso Rocha, et al.. (2007). The PCR-based detection ofTrypanosoma cruziin the faeces ofTriatoma infestansfed on patients with chronic American trypanosomiasis gives higher sensitivity and a quicker result than routine xenodiagnosis. Annals of Tropical Medicine and Parasitology. 101(8). 673–679. 16 indexed citations
20.
Passarelli, Marisa, Sérgio Catanozi, E.R. Nakandakare, et al.. (1999). The diminished rate of mouse peritoneal macrophage cholesterol efflux is not related to the degree of glycation in diabetes mellitus. Atherosclerosis. 144. 44–44. 1 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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